Quantile function. Aka "inverse cdf" or "percent point function".

Given random variable X and p in [0, 1], the quantile is: tfd_quantile(p) := x such that P[X <= x] == p

tfd_quantile(distribution, value, ...)

Arguments

distribution	The distribution being used.
value	float or double Tensor.
...	Additional parameters passed to Python.

Value

a Tensor of shape sample_shape(x) + self$batch_shape with values of type self$dtype.

See also

Other distribution_methods: tfd_cdf(), tfd_covariance(), tfd_cross_entropy(), tfd_entropy(), tfd_kl_divergence(), tfd_log_cdf(), tfd_log_prob(), tfd_log_survival_function(), tfd_mean(), tfd_mode(), tfd_prob(), tfd_sample(), tfd_stddev(), tfd_survival_function(), tfd_variance()

Examples

# \donttest{
  d <- tfd_normal(loc = c(1, 2), scale = c(1, 0.5))
  d %>% tfd_quantile(0.5)
#> tf.Tensor([1. 2.], shape=(2,), dtype=float32)
# }